Simultaneous observations from the Infrared Atmospheric Sounding Interferometer (IASI) and from the Advanced Microwave Sounding Unit (AMSU), launched together onboard the European MetOp platform in October 2006, are used to retrieve an upper tropospheric content of carbon dioxide (CO2) covering...

This paper presents a benchmark for peak detection algorithms employed in fiber Bragg grating spectrometric interrogation systems. The accuracy, precision, and computational performance of currently used algorithms and those of a new proposed artificial neural network algorithm are compared....

In The robustness to noise in speaker identification systems is improved by applying Continuous Wavelet Transform (CWT). In this work, essential speaker features are used to investigate the identification accuracy in non-stationary signals. These features are extracted using Mel Frequency...

We describe a new approach to multiple class pattern classification problems with noise and high dimensional feature space. The approach uses a random matrix X which has a specified distribution with mean M and covariance matrix rij (Î£s, + Î£Îµ) between any two columns of X. When Î£Îµ...

Intuitively one might expect independent noise to be a powerful tool for desynchronizing a population of synchronized neurons. We here show that, intriguingly, for oscillatory neural populations with adaptive synaptic weights governed by spike timing-dependent plasticity (STDP) the opposite is...

In this paper we describe a neural network-based acoustic noise identification procedure. In particular, we have performed some experimental tests on a classic Michelson interferometer used as a microphone, that although different from the VIRGO antenna provides us with global information on the...

This paper presents a recurrent fuzzy-neural filter for adaptive noise cancelation. The cancelation task is transformed to a system-identification problem, which is tackled by use of the dynamic neuron-based fuzzy neural network (DN-FNN). The fuzzy model is based on...

In this paper, two-stage machine learning-based noise detection scheme has been proposed for identification of salt-and- pepper impulse noise which gives excellent detection results for highly corrupted images. In the first stage, a window of size $$3\times 3$$ is taken from image and some other...

The article reports on the significance of neural networks on the online condition of the blades of axial-flow fans monitoring in Europe. The methodology was developed through the utilization of the neural networks trained on features extracted from online blade vibration signals measured on an...